Crude oil evaluation method and device

Abstract

The invention provides a crude oil evaluation method and device. The method comprises the following steps: acquiring molecular composition data of a crude oil sample sent by analysis equipment, wherein the molecular composition data is used for representing content data of each compound in the crude oil sample; based on the molecular composition data, determining molecular characteristic data of the crude oil sample, the molecular characteristic data being used for describing chemical properties of compound molecules contained in the compound; on the basis of the molecular characteristic data, property prediction is conducted on the compound molecules, property prediction data of the compound molecules are obtained, and the property prediction data are used for indicating physical properties of the compound molecules; determining macroscopic physical property data of the crude oil sample based on the molecular characteristic data of the compound molecules and the corresponding property prediction data; and outputting an evaluation result of the crude oil sample, wherein the evaluation result comprises the molecular characteristic data and the macroscopic physical property number. The crude oil evaluation efficiency is improved.

Description

Technical Field

[0001] This application relates to crude oil industry technology, and more particularly to a crude oil evaluation method and apparatus. Background Technology

[0002] With the increasing diversification of crude oil varieties and sources in my country, timely evaluation of crude oil is particularly important for crude oil trading and processing schemes. Moreover, determining a processing scheme for crude oil is the primary task of refining enterprises.

[0003] Traditional crude oil evaluation experiments are time-consuming and costly, causing most refineries to lag behind production decisions in terms of evaluation data. This often fails to meet the time and accuracy requirements of production and operational decisions. Therefore, how to quickly evaluate crude oil is a pressing issue in the crude oil industry. Summary of the Invention

[0004] This application provides a crude oil evaluation method and apparatus to address the problem that existing crude oil evaluation technologies are insufficient to meet the needs of production and operational decision-making.

[0005] On one hand, this application provides a crude oil evaluation method for processing equipment, including:

[0006] The molecular composition data of the crude oil sample sent by the analysis equipment is acquired, and the molecular composition data is used to characterize the content of each compound in the crude oil sample.

[0007] Based on the molecular composition data, the molecular characteristic data of the crude oil sample are determined, and the molecular characteristic data is used to describe the chemical properties of the compound molecules contained in the compound.

[0008] Based on the molecular feature data, the properties of the compound molecules are predicted to obtain property prediction data for each compound molecule. The property prediction data is used to indicate the physical properties of the compound molecules.

[0009] Based on the molecular characteristic data of the compound molecules and the corresponding property prediction data, the macroscopic physical property data of the crude oil sample are determined.

[0010] The evaluation results of the crude oil sample are output, including the molecular characteristic data and the macroscopic physical properties.

[0011] In one possible implementation, the analytical apparatus includes a component separation apparatus, a chemical reaction apparatus, a gas chromatography apparatus, and a high-resolution mass spectrometry apparatus.

[0012] The molecular composition data includes the content data of the target monomer compound, the content data of non-hydrocarbon compounds, and the content data of hydrocarbon compounds; the target monomer compound includes monomer compounds with a boiling point not higher than n-octane, n-alkanes, monocyclic aromatic hydrocarbons, and polycyclic aromatic hydrocarbons; the non-hydrocarbon compounds include nitrogen-containing compounds, sulfur-containing compounds, and oxygen-containing compounds; the hydrocarbon compounds include saturated hydrocarbon compounds and aromatic hydrocarbon compounds;

[0013] The acquisition of molecular composition data of crude oil samples sent by the analytical device includes:

[0014] The gas chromatograph analyzer acquires the content data of the monomeric compound, the content data of the n-alkane, the content data of the monocyclic aromatic hydrocarbon, and the content data of the polycyclic aromatic hydrocarbon; wherein, the content data of the target monomeric compound are obtained by the gas chromatograph analyzer after performing gas chromatographic detection on the light hydrocarbon component, the saturated hydrocarbon component, and the aromatic hydrocarbon component, respectively, and the light hydrocarbon component, the saturated hydrocarbon component, and the aromatic hydrocarbon component are obtained by the component separation device after separating the components of the crude oil sample;

[0015] The method acquires the content data of the non-hydrocarbon compounds, the content data of the hydrocarbon compounds, and the resulting detection data sent by the high-resolution mass spectrometry analysis device. The content data of the non-hydrocarbon compounds and the content data of the hydrocarbon compounds are obtained by the high-resolution mass spectrometry analysis device performing high-resolution mass spectrometry detection on the nitrogen-containing compounds, oxygen-containing compounds, derivatives of sulfur-containing compounds, derivatives of saturated hydrocarbon compounds, and derivatives of aromatic hydrocarbon compounds. The derivatives of sulfur-containing compounds, derivatives of saturated hydrocarbon compounds, and derivatives of aromatic hydrocarbon compounds are all obtained by the chemical reaction device after corresponding conversions of the sulfur-containing compounds, saturated hydrocarbon compounds, and aromatic hydrocarbon compounds.

[0016] In one possible implementation, the nitrogen-containing compound includes basic nitrogen compounds and non-basic nitrogen compounds, and the molecular characteristic data includes quantitative molecular composition data describing the mass fraction of compound molecules;

[0017] The determination of molecular characteristic data of the crude oil sample based on the molecular composition data includes:

[0018] The total nitrogen content is allocated to the basic nitrogen compound and the non-basic nitrogen compound according to a preset ratio;

[0019] The nitrogen atom characteristics of nitrogen atoms are obtained, including the number of first nitrogen atoms, the number of second nitrogen atoms, and the relative molecular mass of the nitrogen atoms. The first nitrogen atom data is used to characterize the number of nitrogen atoms contained in the basic nitrogen compound molecule corresponding to the basic nitrogen compound, and the second nitrogen atom data is used to characterize the number of nitrogen atoms contained in the non-basic nitrogen compound molecule corresponding to the non-basic nitrogen compound.

[0020] Based on the nitrogen atom characteristics, the total nitrogen content in the molecular composition data, the content data of the nitrogen-containing compounds, and the first detection data, the mass fraction of the basic nitrogen compound molecules and the mass fraction of the non-basic nitrogen compound molecules are determined respectively, wherein the first detection data is used to indicate the peak intensity of the basic nitrogen compound molecules and the peak intensity of the non-basic nitrogen compound molecules.

[0021] In one possible implementation, both the basic nitrogen compound and the non-basic nitrogen compound contain polyatomic nitrogen compounds; determining the molecular characteristic data of the crude oil sample based on the molecular composition data includes:

[0022] The mass fraction of the polyatomic nitrogen compound is determined based on the mass fraction of the basic nitrogen compound molecules and the mass fraction of the non-basic nitrogen compound molecules.

[0023] Based on the mass fraction of the polyatomic nitrogen-containing compound, the total oxygen content and total sulfur content in the molecular composition data, the sulfur content to be analyzed and the oxygen content to be analyzed in the crude oil sample are determined. The sulfur content to be analyzed is used to indicate the sulfur content of sulfur-containing compounds that do not contain nitrogen atoms, and the oxygen content to be analyzed is used to indicate the oxygen content of oxygen-containing compounds that do not contain nitrogen atoms.

[0024] Obtain sulfur atom features for describing the physical characteristics of the sulfur atoms and oxygen atom features for describing the physical characteristics of the oxygen atoms;

[0025] Based on the sulfur atom characteristics, the sulfur content to be analyzed, the content data of the sulfur-containing compound, and the second detection data, the mass fraction of sulfur-containing compound molecules that do not contain nitrogen atoms is determined, wherein the second detection data is used to indicate the peak intensity of the sulfur-containing compound molecules.

[0026] Based on the oxygen atom characteristics, the oxygen content to be analyzed, the content data of the oxygen-containing compound, and the third detection data, the mass fraction of oxygen-containing compound molecules that do not contain nitrogen atoms is determined, wherein the third detection data is used to indicate the peak intensity of the oxygen-containing compound molecules.

[0027] In one possible implementation, determining the molecular characteristic data of the crude oil sample based on the molecular composition data includes:

[0028] Based on the peak area of ​​hydrocarbon compounds indicated by the fourth detection data, they are allocated according to a specified ratio to obtain the mass fraction of saturated hydrocarbons and the mass fraction of aromatic hydrocarbons.

[0029] Based on the content data of the target monomer compound, the mass fraction of the monomer compound molecules corresponding to the n-alkane, the monocyclic aromatic hydrocarbon and the polycyclic aromatic hydrocarbon are determined respectively.

[0030] The total mass fraction of saturated hydrocarbon molecules is determined based on the mass fraction of the saturated hydrocarbons and the mass fraction of the monomeric compound molecules corresponding to the n-alkane.

[0031] The total mass fraction of aromatic hydrocarbon molecules is determined based on the mass fraction of the aromatic hydrocarbons, the mass fraction of the monomeric compound molecules corresponding to the monocyclic aromatic hydrocarbons, and the mass fraction of the monomeric compound molecules corresponding to the polycyclic aromatic hydrocarbons.

[0032] The mass fraction of hydrocarbon molecules is determined based on the peak intensity of the hydrocarbon molecules indicated by the fourth detection data, the relative molecular mass of the corresponding hydrocarbon molecules, the total mass fraction of the saturated hydrocarbon molecules, and the total mass fraction of the aromatic hydrocarbon molecules.

[0033] In one possible implementation, the molecular feature data includes molecular structure data, which is used to describe the molecular structure of the compound molecule, and the quantitative molecular composition data further includes the molecular formula, compound type, and equivalent number of double bonds of the compound molecule.

[0034] The step of determining the molecular characteristic data of the crude oil sample based on the molecular composition data further includes:

[0035] Based on the compound type and equivalent number of double bonds of any compound molecule, the compound molecule is matched with a molecular structure library and a side chain library, respectively. The molecular structure library stores one or more molecular core structures, and the side chain library stores one or more side chains.

[0036] The matching results of the molecular structure library and the side chain library are randomly combined until the quantitative molecular composition data of the combined molecular structures are consistent with the quantitative molecular composition data of the compound molecules.

[0037] Based on the combined molecular structure, the structure-guided lumped vector of the compound molecule is determined to generate the molecular structure data of the compound molecule.

[0038] In one possible implementation, the macroscopic physical property data of the crude oil sample includes kinematic viscosity. Determining the macroscopic physical property data of the crude oil sample based on the molecular characteristic data of the compound molecules and corresponding property prediction data includes:

[0039] The first viscosity parameter is calculated based on the target boiling point of the crude oil sample determined by the molecular characteristic data of the crude oil sample.

[0040] The second viscosity parameter is calculated based on the first viscosity parameter and the characteristic coefficients determined by the molecular characteristic data of the crude oil sample.

[0041] Based on the target temperature of the crude oil sample, the first viscosity parameter, and the second viscosity parameter, the first kinematic viscosity value of the crude oil sample is calculated, and the objective function is determined by the difference between the first kinematic viscosity value and the specified second kinematic viscosity value.

[0042] Using a preset partial least squares calculation model, the calculation parameters involved in the first viscosity parameter and the second viscosity parameter are iteratively adjusted to determine the first viscosity parameter and the second viscosity parameter that minimize the objective function, and the first kinematic viscosity value is optimized based on the determined first viscosity parameter and the second viscosity parameter.

[0043] In one possible implementation, the method further includes:

[0044] The crude oil sample is cut according to the molecular characteristic data to obtain at least one cut fraction and corresponding fraction characteristic data, wherein the fraction characteristic data includes the mass fraction of the target compound molecules contained in the cut fraction;

[0045] Based on the mass fraction of the target compound molecule and the target property prediction data of the target compound molecule, the macroscopic physical property data of the cut fraction are determined, wherein the target property prediction data is used to indicate the target physical properties of the target compound molecule.

[0046] In one possible implementation, the step of cutting the crude oil sample based on the molecular characteristic data to obtain at least one cut fraction and corresponding fraction characteristic data includes:

[0047] Based on the characteristics of the first cutting interval of the fraction to be cut and the ratio of the first overlapping interval, a lower limit value of the first control parameter is determined. The first control parameter is used to indicate the cutting of the crude oil sample. The first cutting interval characteristics are used to indicate the upper and lower limits of the first cutting interval. The first cutting interval is determined by the target physical properties of the fraction to be cut. The first overlapping interval ratio is used to characterize the ratio of the first overlapping interval between the specified second cutting interval and the first cutting interval to the first cutting interval. The lower limit value of the first cutting interval is not greater than the upper limit value of the second cutting interval.

[0048] Based on the characteristics of the first cutting interval of the fraction to be cut and the ratio of the second overlapping interval, the upper limit of the first control parameter is determined, wherein the ratio of the second overlapping interval between the specified third cutting interval and the first cutting interval is used to characterize the ratio of the second overlapping interval to the first cutting interval, and the lower limit of the third cutting interval is not greater than the upper limit of the first cutting interval.

[0049] Based on the characteristics of the first cutting interval of the fraction to be cut, the ratio of the first overlapping interval, and the lower limit of the first control parameter, a lower limit of the second control parameter is determined. The second control parameter is used to indicate the cutting of the crude oil sample.

[0050] Based on the characteristics of the first cutting interval of the fraction to be cut, the ratio of the second overlapping interval, and the upper limit of the first control parameter, the upper limit of the second control parameter is determined.

[0051] Based on the lower and upper limits of the first control parameter and the lower and upper limits of the second control parameter, the cutting factor used for cutting is determined;

[0052] Based on the quantitative molecular composition data of the crude oil sample and the cutting factor, the fractional characteristic data of each cut fraction are determined.

[0053] Secondly, this application provides a crude oil evaluation device, comprising:

[0054] The data acquisition module is used to acquire the molecular composition data of the crude oil sample sent by the analysis equipment. The molecular composition data is used to characterize the content of each compound in the crude oil sample.

[0055] A molecular composition analysis module is used to determine the molecular characteristic data of the crude oil sample based on the molecular composition data, wherein the molecular characteristic data is used to describe the chemical properties of the compound molecules contained in the compound.

[0056] The property prediction module is used to predict the properties of the compound molecules based on the molecular feature data, and to obtain property prediction data for each compound molecule. The property prediction data is used to indicate the physical properties of the compound molecules.

[0057] The macroscopic property determination module is used to determine the macroscopic property data of the crude oil sample based on the molecular characteristic data of the compound molecules and the corresponding property prediction data.

[0058] The evaluation output module is used to output the evaluation results of the crude oil sample, the evaluation results including the molecular characteristic data and the macroscopic physical property data.

[0059] The crude oil evaluation method and apparatus provided in this application analyze the molecular characteristic data of crude oil samples to determine the chemical properties of any compound molecule contained in the crude oil sample, and predict the physical properties of the compound molecule and the macroscopic properties of the crude oil sample based on the molecular characteristic data, thus achieving a comprehensive understanding of the properties of crude oil. This eliminates the need for multiple experiments to analyze the chemical and physical properties of crude oil, improving the efficiency of determining crude oil properties. It enables rapid acquisition of crude oil evaluation data to provide accurate and detailed basic data for crude oil planning optimization and production processing schemes, solving the problem that existing crude oil evaluation technologies cannot meet the needs of production and operational decision-making. Attached Figure Description

[0060] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0061] Figure 1 A schematic diagram of a computer architecture provided for an embodiment of this application;

[0062] Figure 2 A schematic diagram of the data processing platform architecture provided in the embodiments of this application;

[0063] Figure 3 A flowchart illustrating a crude oil evaluation method provided in this application embodiment;

[0064] Figure 4 A schematic flowchart illustrating a method for molecular characterization analysis of nitrogen-containing compounds provided in this application embodiment;

[0065] Figure 5 A schematic flowchart illustrating a method for molecular characterization of sulfur-containing and oxygen-containing compounds provided in this application embodiment;

[0066] Figure 6 A schematic flowchart illustrating a method for molecular characterization analysis of hydrocarbon compounds provided in this application embodiment;

[0067] Figure 7 A schematic flowchart of a molecular structure analysis method provided in this application embodiment;

[0068] Figure 8 A schematic flowchart of a crude oil sample kinematic viscosity analysis provided as an exemplary embodiment of this application;

[0069] Figure 9 A schematic flowchart of a method for analyzing the cut fractions of a crude oil sample, provided as an exemplary embodiment of this application;

[0070] Figure 10A schematic diagram of a first cutting interval, a second cutting interval, and a third cutting interval provided for an exemplary embodiment of this application;

[0071] Figure 11 A schematic diagram of a reversible lumped method for a fractionation process provided as an exemplary embodiment of this application;

[0072] Figure 12 This is a schematic diagram of the structure of a crude oil evaluation device provided in an embodiment of this application.

[0073] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0074] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0075] First, let me explain the terms used in this application:

[0076] Hydrocarbons are a general term for compounds composed of carbon and hydrogen atoms. They mainly include alkanes, cycloalkanes, alkenes, alkynes, and aromatic hydrocarbons.

[0077] Non-hydrocarbon compounds: These refer to the impurities such as sulfur, nitrogen, and oxygen that make up petroleum.

[0078] Saturated hydrocarbons refer to alkanes, whose molecules contain only carbon and hydrogen atoms, and all carbon-carbon bonds are single bonds.

[0079] Gas chromatography (GC) is a chromatographic separation and analysis method that uses gas as the mobile phase.

[0080] High-resolution mass spectrometry (HRMS) is a high-resolution mass spectrometry technique that can measure the mass-to-charge ratio (m / z) of ions with very high accuracy, thereby enabling precise identification and quantitative analysis of molecules.

[0081] Distillate fraction: refers to the mixture obtained by distilling liquids such as petroleum at different temperature ranges during the fractionation process.

[0082] Currently, under laboratory conditions, a series of analyses and distillation experiments are conducted on crude oil to understand its properties, composition, and type, and to estimate the yield and quality of straight-run products, providing fundamental data for selecting a suitable petroleum refining process. Specifically, chemical properties are typically determined through experiments such as elemental analysis, sulfur content determination, nitrogen content determination, acid and base value determination, chromatographic analysis, and mass spectrometry, while physical properties are determined primarily through experiments such as density determination, viscosity determination, and freezing point determination. Furthermore, crude oil evaluation also requires experiments such as true boiling point distillation and narrow fraction property determination.

[0083] Therefore, existing crude oil evaluation methods involve multiple experiments, which are inherently complex. It's important to note that crude oil evaluation experiments often require considerable time; for example, processes like true boiling point distillation can last for several days or even longer, significantly impacting evaluation efficiency. Furthermore, because the experiments involve multiple steps and stages, errors at any step can affect the final evaluation result, making it difficult to guarantee the accuracy of the crude oil evaluation.

[0084] Based on the above problems, this application analyzes the molecular composition characteristics of crude oil to determine its chemical properties, and then uses this to predict the physical properties of compounds in crude oil, thereby obtaining the macroscopic physical properties of crude oil. This eliminates the need for multiple experiments, improving the efficiency of crude oil evaluation while ensuring its accuracy.

[0085] The execution subject of this application embodiment may be any electronic device with data processing capabilities (such as the processing device described in this application) and any electronic device with functions such as chromatographic analysis, mass spectrometry analysis, component separation, and chemical reaction experiment (such as the analysis device described in this application).

[0086] For example, Figure 1 This is a schematic diagram of a computer architecture provided in an embodiment of this application. The method of this embodiment can be applied to a computer architecture 100 including a processing device 120 and an analysis device 110. The analysis device 110 performs chromatographic analysis, mass spectrometry analysis, component separation, and chemical reaction tests on crude oil samples to obtain the molecular composition characteristics of the crude oil samples. The analysis device 110 includes a component separation device 111, a chemical reaction device 113, a gas chromatography analysis device 112, and a high-resolution mass spectrometry analysis device 114. Subsequently, the processing device 120 determines the chemical and physical properties of the crude oil samples based on their molecular composition characteristics, thereby evaluating the crude oil samples.

[0087] The execution entity of this application embodiment can also be, for example, a data processing platform equipped with any electronic device having functions such as chromatographic analysis, mass spectrometry analysis, component separation, and chemical reaction experiments. It should be noted that the data processing platform can be deployed separately on an electronic device in any environment (e.g., deployed separately on an edge server in an edge environment), or it can be deployed entirely in a cloud environment, or it can be distributed and deployed in different environments.

[0088] For example, a data processing platform can be logically divided into multiple parts, each with different functions. These parts can be deployed in any two or three of the following environments: electronic devices (located on the user side), edge environments, and cloud environments. An edge environment is defined as a collection of edge electronic devices located close to the electronic devices, including edge servers and edge stations with computing power. The various parts of the data processing platform deployed in different environments or devices work together to achieve the platform's functions.

[0089] It should be understood that this application does not restrict the specific deployment environment of which parts of the data processing platform are deployed. In actual application, the deployment can be adapted according to the computing power of electronic devices, the resource availability of edge and cloud environments, or specific application requirements.

[0090] For example, Figure 2 This is a schematic diagram of the data processing platform architecture provided in the embodiments of this application. The method of the embodiments of this application can be applied to the data processing platform 200. The data processing platform 200 can be deployed on electronic device 201 and cloud environment. The electronic device can be configured as any electronic device with functions such as chromatographic analysis, mass spectrometry analysis, component separation, and chemical reaction experiment. The cloud environment can be configured with cloud server 202.

[0091] Specifically, the molecular composition characteristics of the crude oil sample are obtained through electronic device 201 and communicated with the cloud server 202. Based on the molecular composition characteristics of the crude oil sample, the cloud server 202 determines the chemical and physical properties of the crude oil sample, thereby enabling the analysis and evaluation of the crude oil sample.

[0092] The crude oil evaluation method provided in this application aims to solve the above-mentioned technical problems of the prior art.

[0093] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0094] Figure 3This is a schematic flowchart of a crude oil evaluation method provided in an embodiment of this application. The crude oil evaluation method is used in a processing device and includes steps S301 to S305.

[0095] S301. Obtain the molecular composition data of the crude oil sample sent by the analysis device, wherein the molecular composition data is used to characterize the content of each compound in the crude oil sample.

[0096] It should be noted that the analytical equipment performs chemical analyses on the crude oil sample, such as high-resolution mass spectrometry and gas chromatography, and sends the corresponding results to the processing equipment. These results may include molecular composition data of the crude oil sample, which describes the content of one or more compounds contained within the sample. This compound content data may include component information (such as the compound's components and elements), mass fraction (such as mass percentage), mole fraction, concentration (such as mg / mL, μg / L), and purity.

[0097] In this application, the compounds in the crude oil sample may include hydrocarbon compounds and non-hydrocarbon compounds. The non-hydrocarbon compounds include nitrogen-containing compounds (such as pyridine, pyrrole, etc.), sulfur-containing compounds (such as thiols, thioethers, thiophenes, etc.), and oxygen-containing compounds (such as alcohols, ketones, acids, etc.). The hydrocarbon compounds include saturated hydrocarbon compounds (such as alkanes, cycloalkanes) and aromatic hydrocarbon compounds (such as benzene, toluene, xylene, etc.). Molecular composition data may include total nitrogen content, total oxygen content, and total sulfur content, and may also include content data of the target monomer compound, content data of non-hydrocarbon compounds, and content data of hydrocarbon compounds.

[0098] Among them, the target monomer compounds include monomer compounds with boiling points no higher than n-octane, n-alkanes (such as C4-C40 n-alkanes), monocyclic aromatics (such as C0-C4 alkyl-substituted monocyclic aromatics), and polycyclic aromatics (such as C0-C4 alkyl-substituted polycyclic aromatics).

[0099] S302. Based on the molecular composition data, determine the molecular characteristic data of the crude oil sample, wherein the molecular characteristic data is used to describe the chemical properties of the compound molecules contained in the compound.

[0100] In this application, the chemical properties of crude oil samples, such as chemical composition, composition content, and molecular structure, can be obtained through molecular characteristic data of the crude oil samples. This molecular characteristic data includes, but is not limited to, quantitative molecular composition data describing the mass fraction of compound molecules and molecular structure data describing the molecular structure of compound molecules.

[0101] S303. Based on the molecular characteristic data, the properties of the compound molecules are predicted to obtain property prediction data for each compound molecule. The property prediction data is used to indicate the physical properties of the compound molecules.

[0102] In this application, property prediction can be performed through methods such as list data matching and machine learning models, without limitation. The physical properties of compound molecules can include state (i.e., solid, liquid, or gaseous), melting point, boiling point, density, solubility, refractive index, electrical conductivity, magnetism, polarizability, etc. The prediction of physical properties is based on the molecular characteristic data (i.e., chemical properties) of compound molecules. For example, the state of a compound molecule depends on the strength of the intermolecular forces (such as van der Waals forces, hydrogen bonds, ionic bonds, etc.), and the melting and boiling points of the compound molecule are determined by the strength of the intermolecular interactions.

[0103] S304. Based on the molecular characteristic data of the compound molecules and the corresponding property prediction data, determine the macroscopic physical property data of the crude oil sample.

[0104] In this application, macroscopic physical property data (i.e., physical properties of crude oil samples) are determined based on the physical and chemical properties of compound molecules. These macroscopic physical property data include, but are not limited to, color, appearance, density, kinematic viscosity, pour point, and solubility.

[0105] S305. Output the evaluation results of the crude oil sample, the evaluation results including the molecular characteristic data and the macroscopic physical property data.

[0106] The crude oil evaluation method provided in this application analyzes the molecular characteristic data of crude oil samples to determine the chemical properties of any compound molecule contained in the crude oil sample, and predicts the physical properties of the compound molecule and the macroscopic properties of the crude oil sample based on the molecular characteristic data, thus achieving a comprehensive understanding of the properties of crude oil. This eliminates the need for multiple experiments to analyze the chemical and physical properties of crude oil, improving the efficiency of determining crude oil properties and enabling rapid acquisition of accurate and detailed basic data for crude oil planning optimization and production processing schemes.

[0107] In one possible embodiment, the analytical device may include a component separation device, a chemical reaction device, a gas chromatography analysis device, and a high-resolution mass spectrometry analysis device. The component separation device extracts and quantifies the components of the crude oil sample, such as light hydrocarbon components, saturated hydrocarbon components, and aromatic hydrocarbon components. The gas chromatography analysis device performs gas chromatography detection on the crude oil sample to obtain the content data of the target monomer compound. The chemical reaction device converts sulfur-containing compounds, saturated hydrocarbon compounds, and aromatic hydrocarbon compounds into corresponding derivatives. The high-resolution mass spectrometry analysis device performs high-resolution mass spectrometry detection on the crude oil sample to obtain the content data of non-hydrocarbon compounds and hydrocarbon compounds. The detection results output by the analytical device are then integrated and sent to a processing device. More specifically, step S301 in this application includes:

[0108] Light hydrocarbon components, saturated hydrocarbon components, and aromatic hydrocarbon components were separated from the crude oil sample.

[0109] The gas chromatograph analyzer acquires the content data of the monomeric compound, the content data of the n-alkane, the content data of the monocyclic aromatic hydrocarbon, and the content data of the polycyclic aromatic hydrocarbon; wherein, the content data of the target monomeric compound are obtained by the gas chromatograph analyzer after performing gas chromatographic detection on the light hydrocarbon component, the saturated hydrocarbon component, and the aromatic hydrocarbon component, respectively, and the light hydrocarbon component, the saturated hydrocarbon component, and the aromatic hydrocarbon component are obtained by the component separation device after separating the components of the crude oil sample;

[0110] The method acquires the content data of the non-hydrocarbon compounds, the content data of the hydrocarbon compounds, and the resulting detection data sent by the high-resolution mass spectrometry analysis device. The content data of the non-hydrocarbon compounds and the content data of the hydrocarbon compounds are obtained by the high-resolution mass spectrometry analysis device performing high-resolution mass spectrometry detection on the nitrogen-containing compounds, oxygen-containing compounds, derivatives of sulfur-containing compounds, derivatives of saturated hydrocarbon compounds, and derivatives of aromatic hydrocarbon compounds. The derivatives of sulfur-containing compounds, derivatives of saturated hydrocarbon compounds, and derivatives of aromatic hydrocarbon compounds are all obtained by the chemical reaction device after corresponding conversions of the sulfur-containing compounds, saturated hydrocarbon compounds, and aromatic hydrocarbon compounds.

[0111] In this embodiment, the light hydrocarbon components in the crude oil sample are quantitatively analyzed using a gas chromatography analysis device to obtain the content data of monomeric compounds with a boiling point not higher than that of n-octane.

[0112] Saturated hydrocarbon components and aromatic hydrocarbon components were separated from crude oil samples using a silver ion-modified silica gel column in the component separation device. Subsequently, the saturated hydrocarbon components were quantified using gas chromatography to obtain the content data of C4-C40 n-alkanes. Furthermore, the aromatic hydrocarbon components were quantified using gas chromatography to obtain the content data of C0-C4 alkyl-substituted monocyclic and polycyclic aromatic hydrocarbons.

[0113] Electrospray ionization (ESI) and high-resolution mass spectrometry (HRMS) were combined to selectively analyze nitrogen-containing compounds (such as basic nitrogen compounds and non-basic nitrogen compounds) and oxygen-containing compounds (such as acidic oxygen compounds) in crude oil samples, obtaining the content data of basic nitrogen compounds, non-basic nitrogen compounds, and acidic oxygen compounds in crude oil samples.

[0114] It should be noted that because sulfur-containing compounds (such as sulfides and thiophenes), saturated hydrocarbons, and aromatic hydrocarbons in crude oil samples are nonpolar or weakly polar compounds, they cannot be directly ionized by electrospray ionization. They need to be converted into more polar derivatives through chemical reactions before analysis. In this embodiment, sulfur-containing compounds, saturated hydrocarbons, and aromatic hydrocarbons in crude oil samples are treated using a chemical reaction apparatus according to a pre-set chemical reaction experiment to obtain derivatives of sulfur-containing compounds, saturated hydrocarbons, and aromatic hydrocarbons that can be processed by high-resolution mass spectrometry.

[0115] Furthermore, high-resolution mass spectrometry was used to detect the molecular composition of sulfur-containing compound derivatives, saturated hydrocarbon derivatives, and aromatic hydrocarbon derivatives, thereby obtaining the content data of sulfur-containing compounds, saturated hydrocarbon compounds, and aromatic hydrocarbon compounds in the crude oil sample.

[0116] For example, sulfur-containing compounds are converted into highly polar methyl-sulfoniums using methylation. Aromatic hydrocarbons are converted into strongly polar sulfonates using persulfonation. Saturated hydrocarbons (mainly isoalkanes and cycloalkanes) are selectively converted into alcohols using ruthenium ion-catalyzed oxidation (RICO). These derivatives are then detected by high-resolution mass spectrometry.

[0117] Therefore, this embodiment uses gas chromatography to analyze crude oil samples to obtain the content data of target monomer compounds. Furthermore, nonpolar or weakly polar compounds are converted into more polar derivatives, which are then analyzed by high-resolution mass spectrometry (HMS) to obtain the content data of non-hydrocarbon compounds and hydrocarbon compounds. This allows for detection based on the chemical properties of the compounds, improving the flexibility and comprehensiveness of the detection, ensuring the accuracy of the detected molecular composition data, broadening the application scope of this application, and further improving the accuracy of crude oil evaluation.

[0118] In one possible embodiment, after acquiring the molecular composition data sent by the analytical device, the nitrogen-containing compound is characterized based on the normalization of its elemental composition to obtain molecular characteristic data of the nitrogen-containing compound. The molecular characteristic data includes quantitative molecular composition data describing the mass fraction of the compound molecules. The nitrogen-containing compound includes basic nitrogen compounds and non-basic nitrogen compounds; that is, the quantitative molecular composition data of the nitrogen-containing compound includes the mass fraction of both basic and non-basic nitrogen compounds.

[0119] Specifically, Figure 4 This is a flowchart illustrating a method for molecular characterization of nitrogen-containing compounds provided in this application embodiment. The method includes steps S401 to S403:

[0120] S401. Distribute the total nitrogen content to the alkaline nitrogen compound and the non-alkaline nitrogen compound according to a preset ratio;

[0121] S402. Obtain the nitrogen atom characteristics of nitrogen atoms, wherein the nitrogen atom characteristics include the number of first nitrogen atoms, the number of second nitrogen atoms, and the relative molecular mass of the nitrogen atoms, wherein the first nitrogen atom data is used to characterize the number of nitrogen atoms contained in the basic nitrogen compound molecule corresponding to the basic nitrogen compound, and the second nitrogen atom data is used to characterize the number of nitrogen atoms contained in the non-basic nitrogen compound molecule corresponding to the non-basic nitrogen compound.

[0122] S403. Based on the nitrogen atom characteristics, the total nitrogen content in the molecular composition data, the content data of the nitrogen-containing compound, and the first detection data, determine the mass fraction of the basic nitrogen compound molecule and the mass fraction of the non-basic nitrogen compound molecule, respectively, wherein the first detection data is used to indicate the peak intensity of the basic nitrogen compound molecule and the peak intensity of the non-basic nitrogen compound molecule.

[0123] In this embodiment, based on the normalization of elemental composition, the total nitrogen content in the molecular composition data is allocated to basic nitrogen compounds and non-basic nitrogen compounds according to a preset ratio, for example, the preset ratio can be 1:3. Then, using nitrogen atoms as target heteroatoms, nitrogen atom characteristics are obtained, and based on the nitrogen atom characteristics, the content data of nitrogen-containing compounds, and the first detection data, the mass fraction of any basic nitrogen compound molecule and the mass fraction of any non-basic nitrogen compound molecule are calculated.

[0124] It should be noted that the first detection data comes from the analytical device and is returned to the processing device along with the molecular composition data. This first detection data is used to characterize the mass spectrometry analysis data generated when the high-resolution mass spectrometry analyzer performs high-resolution mass spectrometry detection on nitrogen-containing compounds in crude oil samples. For example, the first detection data may include the peak intensity of any basic nitrogen compound molecule or the peak intensity of any non-basic nitrogen compound molecule.

[0125] Therefore, this embodiment allocates the total nitrogen content to each nitrogen-containing compound, facilitating the determination of the molecular content of each nitrogen-containing compound in crude oil, thereby understanding the specific proportion of each component in the crude oil and improving quantitative accuracy. Furthermore, this embodiment eliminates the need for multiple experiments to quantitatively determine the nitrogen-containing compound content of crude oil, improving the efficiency of crude oil evaluation.

[0126] In one possible embodiment, both the basic nitrogen compounds and the non-basic nitrogen compounds contain polyatomic nitrogen compounds, such as N1O1 and N1S1. Therefore, after obtaining the mass fractions of the basic nitrogen compound molecules and the non-basic nitrogen compound molecules, the mass fractions of sulfur-containing compound molecules and oxygen-containing compound molecules that do not contain nitrogen atoms in the crude oil sample are determined based on the mass fractions of the polyatomic nitrogen compounds and the total oxygen and total sulfur content in the molecular composition data.

[0127] Specifically, Figure 5 This is a flowchart illustrating a method for molecular characterization of sulfur-containing and oxygen-containing compounds provided in this application embodiment. The method includes steps S501 to S505:

[0128] S501. Determine the mass fraction of the polyatomic nitrogen compound based on the mass fraction of the basic nitrogen compound molecules and the mass fraction of the non-basic nitrogen compound molecules;

[0129] S502. Based on the mass fraction of the polyatomic nitrogen-containing compound, the total oxygen content and total sulfur content in the molecular composition data, determine the sulfur content to be analyzed and the oxygen content to be analyzed in the crude oil sample. The sulfur content to be analyzed is used to indicate the sulfur content of sulfur-containing compounds that do not contain nitrogen atoms, and the oxygen content to be analyzed is used to indicate the oxygen content of oxygen-containing compounds that do not contain nitrogen atoms.

[0130] S503. Obtain sulfur atom characteristics for describing the physical characteristics of the sulfur atoms and oxygen atom characteristics for describing the physical characteristics of the oxygen atoms.

[0131] S504. Based on the sulfur atom characteristics, the sulfur content to be analyzed, the content data of the sulfur-containing compound, and the second detection data, determine the mass fraction of sulfur-containing compound molecules that do not contain nitrogen atoms, wherein the second detection data is used to indicate the peak intensity of the sulfur-containing compound molecules.

[0132] S505. Based on the oxygen atom characteristics, the oxygen content to be analyzed, the content data of the oxygen-containing compound, and the third detection data, determine the mass fraction of oxygen-containing compound molecules that do not contain nitrogen atoms, wherein the third detection data is used to indicate the peak intensity of the oxygen-containing compound molecules.

[0133] It should be noted that in step S502, since polyatomic nitrogen compounds are also included in the calculation of the mass fractions of basic and non-basic nitrogen compound molecules, the sulfur and oxygen content of polyatomic nitrogen compounds can be determined based on their mass fractions. Furthermore, by subtracting the sulfur and oxygen content of polyatomic nitrogen compounds from the total oxygen and total sulfur content in the molecular composition data of the crude oil sample, respectively, the sulfur content of sulfur-containing compounds (containing no nitrogen atoms) and the oxygen content of oxygen-containing compounds (containing no nitrogen atoms) can be determined.

[0134] In this application, the second and third detection data can originate from the analytical device and are returned to the processing device along with the molecular composition data. The second detection data is used to characterize the mass spectrometry analysis data generated when the high-resolution mass spectrometry analyzer performs high-resolution mass spectrometry detection on sulfur-containing compounds in crude oil samples, and the third detection data is used to characterize the mass spectrometry analysis data generated when the high-resolution mass spectrometry analyzer performs high-resolution mass spectrometry detection on oxygen-containing compounds in crude oil samples.

[0135] Furthermore, regarding sulfur atoms, sulfur atom characteristics include the relative molecular mass of sulfur atoms and the sulfur atom content, which characterizes the number of sulfur atoms contained in sulfur-containing compound molecules in crude oil samples. Based on these sulfur atom characteristics, the sulfur content of nitrogen-free sulfur-containing compounds, the content data of sulfur-containing compounds in molecular composition data, and the peak intensity of sulfur-containing compound molecules, the mass fraction of nitrogen-free sulfur-containing compound molecules is determined.

[0136] Similarly, for oxygen atoms, oxygen atom characteristics include the relative molecular mass of oxygen atoms and the oxygen atom content, which characterizes the number of oxygen atoms contained in oxygen-containing compound molecules in crude oil samples. Based on these oxygen atom characteristics, the oxygen content of nitrogen-free oxygen-containing compounds, the content data of oxygen-containing compounds in molecular composition data, and the peak intensity of oxygen-containing compound molecules, the mass fraction of nitrogen-free oxygen-containing compound molecules is determined.

[0137] Therefore, this embodiment uses the mass fraction of polyatomic nitrogen-containing compounds to determine the content of sulfur-containing and oxygen-containing compound molecules in crude oil, thereby understanding the specific proportion of each component in the crude oil and improving quantitative accuracy. Furthermore, this embodiment eliminates the need for multiple quantitative experiments, improving the efficiency of crude oil evaluation.

[0138] In an exemplary embodiment, the calculation of the mass fraction of basic nitrogen compound molecules, the mass fraction of non-basic nitrogen compound molecules, the mass fraction of sulfur-containing compound molecules without nitrogen atoms, and the mass fraction of oxygen-containing compound molecules without nitrogen atoms are performed using nitrogen atoms, sulfur atoms, and oxygen atoms as target heteroatoms, respectively. This embodiment provides the following formula (1) to calculate the mass fraction of molecules containing target heteroatoms:

[0139]

[0140] Where, m i1 x represents the mass fraction of molecules containing the target heteroatom (e.g., the mass fraction of sulfur-containing compound molecules that do not contain nitrogen atoms). i I represents the number of target heteroatoms contained in the i-th molecule containing the target heteroatom (e.g., the sulfur atom content used in sulfur atom characteristics to characterize the number of sulfur atoms contained in sulfur-containing compound molecules in crude oil samples). i1 For the detection data corresponding to the target heteroatom (such as second detection data used to indicate the peak intensity of any sulfur-containing compound molecule), C E M represents the elemental content of the target heteroatoms in the crude oil sample (e.g., the sulfur content to be analyzed is used to indicate the sulfur content of sulfur-containing compounds that do not contain nitrogen atoms). e M represents the relative molecular mass of the target heteroatom. i1 This represents the relative molecular mass of the i-th molecule containing the target heteroatom (i.e., the content data of the sulfur-containing compound).

[0141] Therefore, this embodiment calculates the mass fraction of compound molecules using the above formula (1), achieving quantitative calculation of non-hydrocarbon compound molecules in crude oil samples. It is also applicable to calculating the mass fraction of oxygen-containing, sulfur-containing, and nitrogen-containing compound molecules, avoiding errors caused by different calculation methods. Thus, this embodiment improves quantitative accuracy and reliability, further enhancing the accuracy of crude oil evaluation. Furthermore, this embodiment enables rapid and accurate determination of quantitative molecular composition data, significantly shortening analysis time and improving the efficiency of crude oil evaluation.

[0142] In another exemplary embodiment, based on the content data of the target monomer compound in the crude oil sample, the mass fraction of the corresponding monomer compound molecules is obtained, namely, the mass fraction of monomer compounds with a boiling point not higher than n-octane, the mass fraction of n-alkanes, the mass fraction of monocyclic aromatic hydrocarbons, and the mass fraction of polycyclic aromatic hydrocarbons. Specifically, this embodiment provides the following formula (2) for calculation:

[0143]

[0144] Where, m i2 Let m be the mass fraction of the i-th monomer compound molecule. ix Let be the mass fraction of the x-th target monomer compound having the i-th monomer compound molecule, and n be the number of target monomer compounds having the i-th monomer compound molecule.

[0145] Therefore, this embodiment calculates the mass fraction of compound molecules using the above formula (2), thereby realizing the quantitative calculation of monomer compound molecules in crude oil samples, which can improve the quantitative accuracy and further improve the accuracy and efficiency of crude oil evaluation.

[0146] In one possible embodiment, since there is overlap between n-alkanes and saturated hydrocarbons in the target monomer compound, and between monocyclic and polycyclic aromatic hydrocarbons and aromatic hydrocarbons in the target monomer compound, then Figure 6 This is a flowchart illustrating a method for molecular characterization analysis of hydrocarbon compounds provided in an embodiment of this application. The method includes steps S601 to S605:

[0147] S601. Based on the peak area of ​​hydrocarbon compounds indicated by the fourth detection data, allocate them according to a specified ratio to obtain the mass fraction of saturated hydrocarbons and the mass fraction of aromatic hydrocarbons.

[0148] S602. Based on the content data of the target monomer compound, determine the mass fraction of the monomer compound molecules corresponding to the n-alkane, the monocyclic aromatic hydrocarbon, and the polycyclic aromatic hydrocarbon, respectively.

[0149] S603. Determine the total mass fraction of saturated hydrocarbon molecules based on the mass fraction of the saturated hydrocarbon and the mass fraction of the monomeric compound molecules corresponding to the n-alkane.

[0150] S604. Based on the mass fraction of the aromatic hydrocarbons, the mass fraction of the monomeric compound molecules corresponding to the monocyclic aromatic hydrocarbons, and the mass fraction of the monomeric compound molecules corresponding to the polycyclic aromatic hydrocarbons, determine the total mass fraction of the aromatic hydrocarbon molecules.

[0151] S605. Based on the peak intensity of the hydrocarbon compound molecules indicated by the fourth detection data, the relative molecular mass of the corresponding hydrocarbon compound molecules, the total mass fraction of the saturated hydrocarbon molecules, and the total mass fraction of the aromatic hydrocarbon molecules, determine the mass fraction of the hydrocarbon compound molecules.

[0152] In this embodiment, the total mass fraction of saturated hydrocarbon molecules is obtained by subtracting the mass fraction of the target monomer compound corresponding to n-alkane molecules from the mass fraction of saturated hydrocarbons in the hydrocarbon compound. Similarly, the total mass fraction of aromatic hydrocarbon molecules is obtained by subtracting the mass fraction of the target monomer compound corresponding to monocyclic aromatic hydrocarbons and polycyclic aromatic hydrocarbons from the mass fraction of aromatic hydrocarbons in the hydrocarbon compound.

[0153] Furthermore, the mass fraction of saturated hydrocarbon molecules is calculated based on the peak intensity of any saturated hydrocarbon molecule indicated by the fourth detection data, the relative molecular mass of that saturated hydrocarbon molecule, and the total mass fraction of the saturated hydrocarbon molecules. Similarly, the mass fraction of aromatic hydrocarbon molecules is calculated based on the peak intensity of any aromatic hydrocarbon molecule indicated by the fourth detection data, the relative molecular mass of that aromatic hydrocarbon molecule, and the total mass fraction of the aromatic hydrocarbon molecules.

[0154] For example, the mass fraction of hydrocarbon molecules, i.e., the mass fraction of saturated hydrocarbon molecules and the mass fraction of aromatic hydrocarbon molecules, can be calculated using the following formula (3):

[0155]

[0156] Where, m i3 I represents the mass fraction of hydrocarbon molecules. i2 M represents the peak area of ​​hydrocarbon compounds indicated by the fourth detection data. i2m is the relative molecular mass of a hydrocarbon molecule. T It represents the total mass fraction of aromatic hydrocarbon molecules or the total mass fraction of saturated hydrocarbon molecules.

[0157] Therefore, this embodiment determines the total mass fraction of saturated hydrocarbon molecules / aromatic hydrocarbon molecules by removing the mass fraction of monomer molecules corresponding to n-alkane / monocyclic aromatic hydrocarbons and polycyclic aromatic hydrocarbons in the target monomer compound from the mass fraction of saturated hydrocarbons / aromatic hydrocarbons in hydrocarbon compounds. This determines the mass fraction of hydrocarbon compound molecules, avoiding errors caused by data repetition and further improving the quantitative accuracy of hydrocarbon compound molecules.

[0158] In some embodiments, the quantitative molecular composition data further includes the molecular formula, compound type, and equivalent number of double bonds of the compound molecule, and the molecular characteristic data further includes molecular structure data describing the molecular structure of the compound molecule. After determining the quantitative molecular composition data of the compound molecule, the molecular structure of the compound molecule can be determined accordingly, and this molecular structure can be represented using structure-directed lumped aggregation (SOL). Specifically, Figure 7 This is a flowchart illustrating a molecular structure analysis method provided in an embodiment of this application. The method includes steps S701 to S703:

[0159] S701. Based on the compound type and equivalent number of double bonds of any compound molecule, match the compound molecule with a molecular structure library and a side chain library respectively. The molecular structure library stores one or more molecular core structures, and the side chain library stores one or more side chains.

[0160] S702. The matching results of the molecular structure library and the side chain library are randomly combined until the quantitative molecular composition data of the combined molecular structures are consistent with the quantitative molecular composition data of the compound molecules.

[0161] S703. Based on the combined molecular structure, determine the structure-guided lumped vector of the compound molecule to generate the molecular structure data of the compound molecule.

[0162] In this embodiment, the molecular formula of the compound molecule is converted into computer-recognizable and digital information, thereby recording the molecular structure as a structure-oriented lumped vector in the form of structure-oriented lumped (SOL).

[0163] Optionally, for the monomeric compound corresponding to the target monomeric compound, it can be directly converted into a structure-guided lumped vector. It should be noted that multiple monomeric compound molecules may correspond to the same structure-guided lumped vector. In this case, the mass fractions of the monomeric compound molecules represented by the same structure-guided lumped vector can be added together to obtain the mass fraction of the compound corresponding to that structure-guided lumped vector.

[0164] In this embodiment, the molecular structure library stores molecular core structures, which can be the core structural part of a small molecule or compound and play a crucial role in the overall function and properties of the molecule. The side chain library stores side chains, such as straight-chain alkanes, branched alkanes, and alkanes with multiple substituent positions on the ring.

[0165] Therefore, by matching the compound type and equivalent double bond number of a molecule with molecular structure libraries and side chain libraries, the core molecular structure of the molecular structure library and the side chains of the side chain library are randomly combined. Furthermore, the combined molecular structure is compared with the original compound molecule, specifically comparing their compound type and equivalent double bond number. If they match, their molecular formulas are compared. Even further, when the compound type, equivalent double bond number, and molecular formula are all consistent, the structure-guided aggregate vector of the compound molecule is obtained based on the molecular structure corresponding to the combined molecular formula, and this vector serves as the molecular structure data of the compound molecule.

[0166] Therefore, in this embodiment, the quantitative molecular composition data of compound molecules is matched with molecular structure libraries and side chain libraries, and the determined matching results are output as molecular structure data of compound molecules, so as to realize the rapid determination of molecular structure, improve the accuracy and efficiency of molecular structure, and further improve the efficiency of crude oil evaluation.

[0167] In an optional embodiment, in step S303, the properties of the compound molecule can be predicted using a machine learning model. It should be noted that this machine learning model includes, but is not limited to, artificial neural networks, random forests, support vector machines, etc. This machine learning model is used to determine the physical properties of the compound molecule based on the characteristic relationships of its molecular structure data. The molecular structure data of the compound molecule is used as input to this machine learning model, and the output of the machine learning model is the property prediction result for the physical properties of the compound molecule. For example, the machine learning model determines the melting point and boiling point of the compound molecule by analyzing the strength of the interactions between compound molecules.

[0168] Optionally, the machine learning model can be trained using a training dataset. The training dataset may include a first training subset obtained from conventional physical property experimental data, and a second training subset obtained from conventional physical property experimental data using empirical correlation fitting, specifically for high-carbon-number molecules or polycyclic molecules.

[0169] For example, conventional physical property experimental data of compound molecules in crude oil samples are obtained, including boiling point, critical temperature, critical pressure, octane number, viscosity, etc. The molecular characteristic data of the compound molecules in the crude oil samples are used as sample data, and the physical properties of the compound molecules in the crude oil samples are used as labels to obtain the first training subset.

[0170] Since experimental data on high-carbon-number or polycyclic molecules are lacking, empirical correlations using the following formula (4) can be used to fit and obtain the physical property fitting data for these molecules:

[0171] p = ∑ i N i ·p i +a·lnnC (4)

[0172] Where p represents the physical properties of the compound molecule, nC represents the total number of carbon atoms in the compound molecule, and N i p represents the number of i-groups (e.g., CH3, CH2, etc.) in a compound molecule. i The contribution value of the i-group.

[0173] Furthermore, the molecular characteristic data of high carbon number or polycyclic molecules in crude oil samples are used as sample data, and the physical property fitting data of the target properties of high carbon number or polycyclic molecules obtained by formula (4) are used as labels to obtain the second training subset.

[0174] Furthermore, a training dataset and a test set are used. The training dataset is used to train the hyperparameters of the machine learning model, and the test set is used to test the generalization performance of the machine learning model. By balancing the errors of the training dataset and the prediction set, a machine learning model with good performance can be obtained.

[0175] Optionally, during training, a loss function (e.g., root mean square error function) is established to calculate the difference between the predicted value and the label. An optimization algorithm (e.g., gradient descent) is then used to continuously adjust the hyperparameters of the machine learning model, such as the number of hidden layers and hidden nodes, to reduce the value of the loss function until the model converges, resulting in the trained model.

[0176] In some embodiments, after determining the property prediction data of the compound molecules, the macroscopic physical property data of the crude oil sample are determined by combining the molecular characteristic data of the crude oil sample. The macroscopic physical property data includes, but is not limited to, color, appearance, density, kinematic viscosity, pour point, solubility, etc.

[0177] Optionally, the macroscopic property data of the crude oil sample can be determined by a macroscopic property prediction model. This model is used to determine the macroscopic properties of the crude oil sample based on the correlation of the physical properties of compound molecules. For example, the physical properties (such as molecular weight and density) of various compound molecules contained in the crude oil sample have a linear relationship, and there will be no positive or negative effect when they are mixed. The macroscopic property prediction model is determined using the following formula (5):

[0178]

[0179] Among them, P b For the macroscopic physical property data of crude oil samples, R i Let P be the mass fraction of the i-th compound molecule in the crude oil sample. i The predicted properties (e.g., physical properties) of the i-th compound molecule are given, where k is the number of compound molecules in the crude oil sample.

[0180] It should be noted that the macroscopic properties of crude oil samples may exhibit positive or negative effects upon mixing. These macroscopic properties can be accurately obtained by fitting the mixture using nonlinear mixing rules. The nonlinear mixing rule includes the form of the mixing equation used to fit the macroscopic properties of the crude oil sample, as well as the parameters of this mixing equation obtained by fitting a large amount of experimental data. The accurate form of the mixing equation and the combination of parameters determine the accuracy of the nonlinear model predictions obtained based on the nonlinear mixing rule.

[0181] Therefore, this embodiment analyzes the correlation between compound molecules in crude oil samples through a macroscopic property prediction model, thereby determining the macroscopic properties of crude oil samples and improving the accuracy of crude oil evaluation.

[0182] In one example embodiment, the macroscopic property of the crude oil sample may be kinematic viscosity. Figure 8 This is a schematic flowchart illustrating the kinematic viscosity analysis of a crude oil sample as provided in an exemplary embodiment of this application. This embodiment provides a method for kinematic viscosity analysis of a crude oil sample, including steps S801 to S804:

[0183] S801. Calculate the first viscosity parameter based on the target boiling point of the crude oil sample determined by the molecular characteristic data of the crude oil sample.

[0184] S802. Calculate the second viscosity parameter based on the first viscosity parameter and the characteristic coefficients determined by the molecular characteristic data of the crude oil sample;

[0185] S803. Based on the target temperature of the crude oil sample, the first viscosity parameter, and the second viscosity parameter, calculate the first kinematic viscosity value of the crude oil sample, and determine the objective function by the difference between the first kinematic viscosity value and the specified second kinematic viscosity value.

[0186] S804. Using a preset partial least squares calculation model, iteratively adjust the calculation parameters involved in the first viscosity parameter and the second viscosity parameter to determine the first viscosity parameter and the second viscosity parameter that minimize the objective function, and optimize the first kinematic viscosity value based on the determined first viscosity parameter and the second viscosity parameter.

[0187] For example, the first viscosity parameter is calculated using the following formula (6), and the second viscosity parameter is calculated using the following formula (7):

[0188] lnA = 4.717 + 0.00526·T b (6)

[0189]

[0190] Where A is the first viscosity parameter, B is the second viscosity parameter, and both A and B contain multiple elements; T b The target boiling point is the crude oil sample after 50% distillation by volume; K is the characteristic coefficient, which can be calculated based on the molecular composition data of the crude oil sample.

[0191] The kinematic viscosity is calculated using the following formula (8):

[0192]

[0193] in, Here, T represents the kinematic viscosity value, and T represents the target temperature of the crude oil sample.

[0194] It is understood that in this embodiment, the objective function is established based on the difference between the first kinematic viscosity value and the second kinematic viscosity value. The second kinematic viscosity value is the kinematic viscosity of the crude oil sample measured experimentally, and the first kinematic viscosity value is the kinematic viscosity of the crude oil sample calculated using the kinematic viscosity calculation formula (8) above. Then, using partial least squares, each element in the first viscosity parameter and each element in the second viscosity parameter are iteratively adjusted. The first viscosity parameter and the second viscosity parameter that minimize the value of the objective function are taken as the final first viscosity parameter A and second viscosity parameter B.

[0195] Therefore, this embodiment improves the accuracy of kinematic viscosity values ​​by iteratively optimizing the first viscosity parameter and the second viscosity parameter, thereby improving the accuracy of crude oil evaluation.

[0196] In one possible embodiment, the crude oil sample is divided into multiple cut fractions. Figure 9 A flowchart illustrating a method for analyzing the cut fraction of a crude oil sample, provided as an exemplary embodiment of this application, describes a method for analyzing the macroscopic properties of the cut fraction. This method includes steps S901 to S902:

[0197] S901. The crude oil sample is cut according to the molecular characteristic data to obtain at least one cut fraction and corresponding fraction characteristic data, wherein the fraction characteristic data includes the mass fraction of the target compound molecules contained in the cut fraction.

[0198] S902. Based on the mass fraction of the target compound molecule and the target property prediction data of the target compound molecule, determine the macroscopic physical property data of the cut fraction, wherein the target property prediction data is used to indicate the target physical properties of the target compound molecule.

[0199] In existing technologies, crude oil samples need to be cut into different fractions such as naphtha, kerosene, diesel, wax oil and residue oil, and then different instruments are used to detect the macroscopic physical property data of each fraction, which requires a large investment of human resources and equipment costs.

[0200] Based on the above, in this embodiment, the macroscopic property data of the cut fraction may include data on various macroscopic physical properties of the cut fraction (e.g., boiling point, kinematic viscosity, etc.). Optionally, each macroscopic physical property of the cut fraction is taken as the target property, and the molecular weight fraction of each cut fraction of the crude oil sample and the target property prediction data of various compound molecules contained in each cut fraction are processed using a macroscopic property prediction model to finally obtain the macroscopic property data of each cut fraction.

[0201] Optionally, the macroscopic properties of the cut fraction can be calculated using the formula (5) above. The macroscopic properties of the cut fraction may exhibit positive or negative effects during mixing, and the macroscopic properties of the cut fraction can be accurately obtained by fitting the nonlinear mixing rules.

[0202] Therefore, this embodiment determines the macroscopic properties of multiple cut fractions by using quantitative molecular composition data of crude oil samples, without the need to conduct experiments on each cut fraction individually, thus improving the efficiency of fraction evaluation, avoiding related errors caused by multiple experiments, and improving accuracy.

[0203] In some embodiments, a preset crude oil cutting algorithm is used to cut the crude oil sample before determining the macroscopic properties of the cut fraction. Specifically, Figure 10 The schematic diagram of a first cutting interval, a second cutting interval, and a third cutting interval provided as an exemplary embodiment of this application shows that the crude oil cutting algorithm includes:

[0204] Based on the characteristics of the first cutting interval of the fraction to be cut and the ratio of the first overlapping interval, a lower limit value of the first control parameter is determined. The first control parameter is used to indicate the cutting of the crude oil sample. The first cutting interval characteristics are used to indicate the upper and lower limits of the first cutting interval. The first cutting interval is determined by the target physical properties of the fraction to be cut. The first overlapping interval ratio is used to characterize the ratio of the first overlapping interval between the specified second cutting interval and the first cutting interval to the first cutting interval. The lower limit value of the first cutting interval is not greater than the upper limit value of the second cutting interval.

[0205] Based on the characteristics of the first cutting interval of the fraction to be cut and the ratio of the second overlapping interval, the upper limit of the first control parameter is determined, wherein the ratio of the second overlapping interval between the specified third cutting interval and the first cutting interval is used to characterize the ratio of the second overlapping interval to the first cutting interval, and the lower limit of the third cutting interval is not greater than the upper limit of the first cutting interval.

[0206] Based on the characteristics of the first cutting interval of the fraction to be cut, the ratio of the first overlapping interval, and the lower limit of the first control parameter, a lower limit of the second control parameter is determined. The second control parameter is used to indicate the cutting of the crude oil sample.

[0207] Based on the characteristics of the first cutting interval of the fraction to be cut, the ratio of the second overlapping interval, and the upper limit of the first control parameter, the upper limit of the second control parameter is determined.

[0208] Based on the lower and upper limits of the first control parameter and the lower and upper limits of the second control parameter, the cutting factor used for cutting is determined;

[0209] Based on the quantitative molecular composition data of the crude oil sample and the cutting factor, the fractional characteristic data of each cut fraction are determined.

[0210] In this embodiment, the target physical property can be the boiling point, so the upper limit of the first cutting interval can be 180 degrees, and the lower limit of the first cutting interval can be 230 degrees. For example, the fractional characteristic data of the cut fraction are determined by the following formula (9), including:

[0211] cut_mass_frac=factor·mass_frac (9)

[0212] Where cut_mass_frac is the fractional characteristic data of the cut fraction, factor is the cut factor, and mass_frac is the quantitative molecular composition data of the crude oil sample.

[0213] Specifically, the cutoff factor is determined using the following formula (10), including:

[0214]

[0215] Among them, z i Let y be the value of the physical property of any compound molecule in the crude oil sample. i x is the parameter for calculating the cutoff factor. lmin x is the lower limit value of the first control parameter. lmax x is the upper limit value of the first control parameter. fmax x is the upper limit value of the second control parameter. fmin This is the lower limit value of the second control parameter.

[0216] More specifically, the lower and upper limits of the first control parameter and the lower and upper limits of the second control parameter are determined by the following formulas (11)-(14), including:

[0217] x lmin =range1-(range2-range1)·front_overlap_ratio (11)

[0218] x lmax =range2+(range2-range1)·last_overlap_ratio (12)

[0219] x fmin =x lmin +(range2-range1)·front_overlap_ratio·2 (13)

[0220] x fmax =x lmax -(range2-range1)·last_overlap_ratio·2 (14)

[0221] Where range1 is the upper limit of the first cutting interval, range2 is the lower limit of the first cutting interval, front_overlap_ratio is the ratio of the first overlapping interval, and last_overlap_ratio is the ratio of the second overlapping interval.

[0222] Therefore, this embodiment achieves the cutting of distillates through the above-described cutting algorithm, thereby improving the rationality and accuracy of distillate cutting.

[0223] Optionally, given the vast number of molecular components in crude oil, to maintain a balance between complexity and accuracy, a reversible lumped method can be used to construct a separation process model. This model can then be used to obtain the mass fraction of each cut fraction of the crude oil sample. This is merely an example. Figure 11 This schematic diagram illustrates a reversible lumping method for fractionation in an exemplary embodiment of this application. First, all molecules in a crude oil sample are lumped together according to their boiling points, resulting in a finite number of lumps that are used for thermodynamic calculations in subsequent separation processes. During the lumping process, the mapping relationship between molecules and lumps is saved. After lumped-level separation is completed, the mapping relationship is applied to the product lumps using an anti-lumping method, yielding the types and distribution of molecules in each product. This process can also utilize the distillation module in existing process simulation software, such as Aspen Plus, allowing the raw material lumps to be input into Aspen Plus via a data interface to simulate the distillation process.

[0224] Figure 12 This is a schematic diagram of a crude oil evaluation device provided in an embodiment of this application. The crude oil evaluation device 1000 includes:

[0225] The data acquisition module 1001 is used to acquire the molecular composition data of the crude oil sample sent by the analysis device, wherein the molecular composition data is used to characterize the content data of each compound in the crude oil sample.

[0226] The molecular composition analysis module 1002 is used to determine the molecular characteristic data of the crude oil sample based on the molecular composition data, wherein the molecular characteristic data is used to describe the chemical properties of the compound molecules contained in the compound.

[0227] Property prediction module 1003 is used to predict the properties of the compound molecules based on the molecular feature data, and obtain property prediction data for each compound molecule. The property prediction data is used to indicate the physical properties of the compound molecules.

[0228] The macroscopic property determination module 1004 is used to determine the macroscopic property data of the crude oil sample based on the molecular characteristic data of the compound molecules and the corresponding property prediction data.

[0229] The evaluation output module 1005 is used to output the evaluation results of the crude oil sample, the evaluation results including the molecular characteristic data and the macroscopic physical property data.

[0230] In some embodiments, the analytical equipment includes component separation equipment, chemical reaction equipment, gas chromatography analysis equipment, and high-resolution mass spectrometry analysis equipment;

[0231] The molecular composition data includes the content data of the target monomer compound, the content data of non-hydrocarbon compounds, and the content data of hydrocarbon compounds; the target monomer compound includes monomer compounds with a boiling point not higher than n-octane, n-alkanes, monocyclic aromatic hydrocarbons, and polycyclic aromatic hydrocarbons; the non-hydrocarbon compounds include nitrogen-containing compounds, sulfur-containing compounds, and oxygen-containing compounds; the hydrocarbon compounds include saturated hydrocarbon compounds and aromatic hydrocarbon compounds;

[0232] The data acquisition module includes:

[0233] The first molecular composition data acquisition unit is used to acquire the content data of the monomeric compound, the content data of the n-alkane, the content data of the monocyclic aromatic hydrocarbon, and the content data of the polycyclic aromatic hydrocarbon sent by the gas chromatography analysis device; wherein, the content data of the target monomeric compound are all obtained by the gas chromatography analysis device after performing gas chromatography detection on the light hydrocarbon component, the saturated hydrocarbon component, and the aromatic hydrocarbon component respectively, and the light hydrocarbon component, the saturated hydrocarbon component, and the aromatic hydrocarbon component are all obtained by the component separation device after separating the components of the crude oil sample;

[0234] The second molecular composition data acquisition unit is used to acquire the content data of the non-hydrocarbon compounds, the content data of the hydrocarbon compounds, and the resulting detection data sent by the high-resolution mass spectrometry analysis device. The content data of the non-hydrocarbon compounds and the content data of the hydrocarbon compounds are obtained by the high-resolution mass spectrometry analysis device after performing high-resolution mass spectrometry detection on the nitrogen-containing compounds, oxygen-containing compounds, derivatives of sulfur-containing compounds, derivatives of saturated hydrocarbon compounds, and derivatives of aromatic hydrocarbon compounds. The derivatives of sulfur-containing compounds, derivatives of saturated hydrocarbon compounds, and derivatives of aromatic hydrocarbon compounds are all obtained by the chemical reaction device after corresponding conversions of the sulfur-containing compounds, saturated hydrocarbon compounds, and aromatic hydrocarbon compounds.

[0235] In some embodiments, the nitrogen-containing compound includes basic nitrogen compounds and non-basic nitrogen compounds, and the molecular characteristic data includes quantitative molecular composition data describing the mass fraction of compound molecules;

[0236] The molecular composition analysis module includes:

[0237] A total nitrogen content distribution unit is used to distribute the total nitrogen content into the alkaline nitrogen compound and the non-alkaline nitrogen compound according to a preset ratio;

[0238] A nitrogen atom feature acquisition unit is used to acquire nitrogen atom features, wherein the nitrogen atom features include a first nitrogen atom quantity, a second nitrogen atom quantity, and the relative molecular mass of the nitrogen atom. The first nitrogen atom data is used to characterize the number of nitrogen atoms contained in the basic nitrogen compound molecule corresponding to the basic nitrogen compound, and the second nitrogen atom data is used to characterize the number of nitrogen atoms contained in the non-basic nitrogen compound molecule corresponding to the non-basic nitrogen compound.

[0239] A molecular characteristic determination unit for nitrogen-containing compounds is used to determine the mass fraction of the basic nitrogen compound molecules and the mass fraction of the non-basic nitrogen compound molecules based on the nitrogen atom characteristics, the total nitrogen content in the molecular composition data, the content data of the nitrogen-containing compound, and the first detection data, wherein the first detection data is used to indicate the peak intensity of the basic nitrogen compound molecules and the peak intensity of the non-basic nitrogen compound molecules.

[0240] In some embodiments, both the basic nitrogen compound and the non-basic nitrogen compound contain polyatomic nitrogen compounds; the molecular composition analysis module includes:

[0241] A molecular characteristic determination unit for polyatomic nitrogen compounds is used to determine the mass fraction of the polyatomic nitrogen compound based on the mass fraction of the basic nitrogen compound molecules and the mass fraction of the non-basic nitrogen compound molecules.

[0242] The element content determination unit is used to determine the sulfur content and oxygen content to be analyzed in the crude oil sample based on the mass fraction of the polyatomic nitrogen-containing compound, the total oxygen content and the total sulfur content in the molecular composition data. The sulfur content to be analyzed is used to indicate the sulfur content of sulfur-containing compounds that do not contain nitrogen atoms, and the oxygen content to be analyzed is used to indicate the oxygen content of oxygen-containing compounds that do not contain nitrogen atoms.

[0243] An atomic feature acquisition unit is used to acquire sulfur atom features for describing the physical characteristics of the sulfur atoms and oxygen atom features for describing the physical characteristics of the oxygen atoms.

[0244] A molecular characteristic determination unit for sulfur-containing compounds is used to determine the mass fraction of sulfur-containing compound molecules that do not contain nitrogen atoms based on the sulfur atom characteristics, the sulfur content to be analyzed, the content data of the sulfur-containing compound, and second detection data, wherein the second detection data is used to indicate the peak intensity of the sulfur-containing compound molecules.

[0245] The unit for determining the molecular characteristics of oxygen-containing compounds is used to determine the mass fraction of oxygen-containing compound molecules that do not contain nitrogen atoms based on the oxygen atom characteristics, the oxygen content to be analyzed, the content data of the oxygen-containing compound, and third detection data, wherein the third detection data is used to indicate the peak intensity of the oxygen-containing compound molecules.

[0246] In some embodiments, the molecular composition analysis module further includes:

[0247] The first unit for determining the molecular characteristics of hydrocarbons is used to allocate them according to a specified ratio based on the peak area of ​​hydrocarbons indicated by the fourth detection data, so as to obtain the mass fraction of saturated hydrocarbons and the mass fraction of aromatic hydrocarbons.

[0248] The molecular characteristic determination unit of the target monomer compound is used to determine the mass fraction of the monomer compound molecules corresponding to the n-alkane, the monocyclic aromatic hydrocarbon and the polycyclic aromatic hydrocarbon based on the content data of the target monomer compound.

[0249] The total mass fraction determination unit of saturated hydrocarbon molecules is used to determine the total mass fraction of saturated hydrocarbon molecules based on the mass fraction of the saturated hydrocarbon and the mass fraction of the monomer compound molecules corresponding to the n-alkane.

[0250] The total mass fraction determination unit of aromatic hydrocarbon molecules is used to determine the total mass fraction of aromatic hydrocarbon molecules based on the mass fraction of the aromatic hydrocarbons, the mass fraction of the monomeric compound molecules corresponding to the monocyclic aromatic hydrocarbons, and the mass fraction of the monomeric compound molecules corresponding to the polycyclic aromatic hydrocarbons.

[0251] The second hydrocarbon compound molecular characteristic determination unit is used to determine the mass fraction of hydrocarbon compound molecules based on the peak intensity of the hydrocarbon compound molecules indicated by the fourth detection data, the relative molecular mass of the corresponding hydrocarbon compound molecules, the total mass fraction of the saturated hydrocarbon molecules, and the total mass fraction of the aromatic hydrocarbon molecules.

[0252] In some embodiments, the molecular feature data includes molecular structure data, which is used to describe the molecular structure of the compound molecule, and the quantitative molecular composition data further includes the molecular formula, compound type, and equivalent number of double bonds of the compound molecule.

[0253] The molecular composition analysis module further includes:

[0254] The database matching unit is used to match any compound molecule with a molecular structure library and a side chain library based on the compound type and the number of equivalent double bonds of the compound molecule. The molecular structure library stores one or more molecular core structures, and the side chain library stores one or more side chains.

[0255] The structural combination unit is used to randomly combine the matching results of the molecular structure library and the side chain library until the quantitative molecular composition data of the combined molecular structures are consistent with the quantitative molecular composition data of the compound molecules.

[0256] The structure-guided lumped vector determination unit is used to determine the structure-guided lumped vector of the compound molecule based on the combined molecular structure, so as to generate the molecular structure data of the compound molecule.

[0257] In some embodiments, the macroscopic physical property data of the crude oil sample includes kinematic viscosity, and the macroscopic physical property determination module includes:

[0258] The first viscosity parameter calculation unit is used to calculate the first viscosity parameter based on the target boiling point of the crude oil sample determined by the molecular characteristic data of the crude oil sample.

[0259] The second viscosity parameter calculation unit is used to calculate the second viscosity parameter based on the first viscosity parameter and the characteristic coefficients determined by the molecular characteristic data of the crude oil sample.

[0260] The first kinematic viscosity calculation unit is used to calculate the first kinematic viscosity value of the crude oil sample based on the target temperature of the crude oil sample, the first viscosity parameter and the second viscosity parameter, and to determine the objective function by the difference between the first kinematic viscosity value and the specified second kinematic viscosity value.

[0261] The iterative unit is used to iteratively adjust the calculation parameters involved in the first viscosity parameter and the second viscosity parameter using a preset partial least squares calculation model, so as to determine the first viscosity parameter and the second viscosity parameter that minimize the objective function, and optimize the first kinematic viscosity value based on the determined first viscosity parameter and the second viscosity parameter.

[0262] In some embodiments, the crude oil evaluation device further includes:

[0263] The crude oil cutting unit is used to cut the crude oil sample according to the molecular characteristic data to obtain at least one cut fraction and corresponding fraction characteristic data, wherein the fraction characteristic data includes the mass fraction of target compound molecules contained in the cut fraction.

[0264] The fraction macroscopic property determination unit is used to determine the macroscopic property data of the cut fraction based on the mass fraction of the target compound molecule and the target property prediction data of the target compound molecule, wherein the target property prediction data is used to indicate the target physical properties of the target compound molecule.

[0265] In some embodiments, the crude oil cutting unit includes:

[0266] The first parameter determining unit is used to determine the lower limit of the first control parameter based on the first cutting interval characteristics and the first overlap interval ratio of the fraction to be cut. The first control parameter is used to indicate the cutting of the crude oil sample. The first cutting interval characteristics are used to indicate the upper and lower limits of the first cutting interval. The first cutting interval is determined by the target physical properties of the fraction to be cut. The first overlap interval ratio is used to characterize the ratio of the first overlap interval between the specified second cutting interval and the first cutting interval to the first cutting interval. The lower limit of the first cutting interval is not greater than the upper limit of the second cutting interval.

[0267] The second parameter determination unit is used to determine the upper limit of the first control parameter based on the characteristics of the first cutting interval of the fraction to be cut and the second overlapping interval ratio, wherein the second overlapping interval ratio is used to characterize the ratio of the second overlapping interval between the specified third cutting interval and the first cutting interval to the first cutting interval, and the lower limit of the third cutting interval is not greater than the upper limit of the first cutting interval.

[0268] The third parameter determination unit is used to determine the lower limit value of the second control parameter based on the first cutting interval characteristics of the fraction to be cut, the first overlapping interval ratio, and the lower limit value of the first control parameter. The second control parameter is used to indicate the cutting of the crude oil sample.

[0269] The fourth parameter determination unit is used to determine the upper limit value of the second control parameter based on the first cutting interval characteristics of the fraction to be cut, the ratio of the second overlapping interval, and the upper limit value of the first control parameter.

[0270] The cutting factor determination unit is used to determine the cutting factor to be used for cutting based on the lower limit and upper limit of the first control parameter and the lower limit and upper limit of the second control parameter.

[0271] The fraction characteristic determination unit is used to determine the fraction characteristic data of each cut fraction based on the quantitative molecular composition data of the crude oil sample and the cutting factor.

[0272] The apparatus in this application embodiment can execute the method provided in this application embodiment, and the implementation principle is similar. The actions performed by each module in the apparatus of each embodiment of this application correspond to the steps in the method of each embodiment of this application. For detailed functional descriptions of each module of the apparatus, please refer to the descriptions in the corresponding methods shown above, which will not be repeated here.

[0273] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0274] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A crude oil evaluation method, characterized in that, For use in processing equipment, including: The molecular composition data of the crude oil sample sent by the analysis equipment is acquired, and the molecular composition data is used to characterize the content of each compound in the crude oil sample. Based on the molecular composition data, the molecular characteristic data of the crude oil sample are determined, and the molecular characteristic data is used to describe the chemical properties of the compound molecules contained in the compound. Based on the molecular feature data, the properties of the compound molecules are predicted to obtain property prediction data for each compound molecule. The property prediction data is used to indicate the physical properties of the compound molecules. Based on the molecular characteristic data of the compound molecules and the corresponding property prediction data, the macroscopic physical property data of the crude oil sample are determined. The evaluation results of the crude oil sample are output, including the molecular characteristic data and the macroscopic physical properties.

2. The crude oil evaluation method according to claim 1, characterized in that, The analytical equipment includes component separation equipment, chemical reaction equipment, gas chromatography analysis equipment, and high-resolution mass spectrometry analysis equipment. The molecular composition data includes the content data of the target monomer compound, the content data of non-hydrocarbon compounds, and the content data of hydrocarbon compounds; the target monomer compound includes monomer compounds with a boiling point not higher than that of n-octane, n-alkanes, monocyclic aromatic hydrocarbons, and polycyclic aromatic hydrocarbons; the non-hydrocarbon compounds include nitrogen-containing compounds, sulfur-containing compounds, and oxygen-containing compounds; The hydrocarbon compounds include saturated hydrocarbon compounds and aromatic hydrocarbon compounds; The acquisition of molecular composition data of crude oil samples sent by the analytical device includes: The gas chromatograph analyzer acquires the content data of the monomeric compound, the content data of the n-alkane, the content data of the monocyclic aromatic hydrocarbon, and the content data of the polycyclic aromatic hydrocarbon; wherein, the content data of the target monomeric compound are obtained by the gas chromatograph analyzer after performing gas chromatographic detection on the light hydrocarbon component, the saturated hydrocarbon component, and the aromatic hydrocarbon component, respectively, and the light hydrocarbon component, the saturated hydrocarbon component, and the aromatic hydrocarbon component are obtained by the component separation device after separating the components of the crude oil sample; The method acquires the content data of the non-hydrocarbon compounds, the content data of the hydrocarbon compounds, and the resulting detection data sent by the high-resolution mass spectrometry analysis device. The content data of the non-hydrocarbon compounds and the content data of the hydrocarbon compounds are obtained by the high-resolution mass spectrometry analysis device performing high-resolution mass spectrometry detection on the nitrogen-containing compounds, oxygen-containing compounds, derivatives of sulfur-containing compounds, derivatives of saturated hydrocarbon compounds, and derivatives of aromatic hydrocarbon compounds. The derivatives of sulfur-containing compounds, derivatives of saturated hydrocarbon compounds, and derivatives of aromatic hydrocarbon compounds are all obtained by the chemical reaction device after corresponding conversions of the sulfur-containing compounds, saturated hydrocarbon compounds, and aromatic hydrocarbon compounds.

3. The crude oil evaluation method according to claim 2, characterized in that, The nitrogen-containing compounds include basic nitrogen compounds and non-basic nitrogen compounds, and the molecular characteristic data includes quantitative molecular composition data used to describe the mass fraction of compound molecules; The determination of molecular characteristic data of the crude oil sample based on the molecular composition data includes: The total nitrogen content is allocated to the basic nitrogen compound and the non-basic nitrogen compound according to a preset ratio; The nitrogen atom characteristics of nitrogen atoms are obtained, including the number of first nitrogen atoms, the number of second nitrogen atoms, and the relative molecular mass of the nitrogen atoms. The first nitrogen atom data is used to characterize the number of nitrogen atoms contained in the basic nitrogen compound molecule corresponding to the basic nitrogen compound, and the second nitrogen atom data is used to characterize the number of nitrogen atoms contained in the non-basic nitrogen compound molecule corresponding to the non-basic nitrogen compound. Based on the nitrogen atom characteristics, the total nitrogen content in the molecular composition data, the content data of the nitrogen-containing compounds, and the first detection data, the mass fraction of the basic nitrogen compound molecules and the mass fraction of the non-basic nitrogen compound molecules are determined respectively, wherein the first detection data is used to indicate the peak intensity of the basic nitrogen compound molecules and the peak intensity of the non-basic nitrogen compound molecules.

4. The crude oil evaluation method according to claim 3, characterized in that, Both the basic nitrogen compound and the non-basic nitrogen compound contain polyatomic nitrogen compounds; the determination of the molecular characteristic data of the crude oil sample based on the molecular composition data includes: The mass fraction of the polyatomic nitrogen compound is determined based on the mass fraction of the basic nitrogen compound molecules and the mass fraction of the non-basic nitrogen compound molecules. Based on the mass fraction of the polyatomic nitrogen-containing compound, the total oxygen content and total sulfur content in the molecular composition data, the sulfur content to be analyzed and the oxygen content to be analyzed in the crude oil sample are determined. The sulfur content to be analyzed is used to indicate the sulfur content of sulfur-containing compounds that do not contain nitrogen atoms, and the oxygen content to be analyzed is used to indicate the oxygen content of oxygen-containing compounds that do not contain nitrogen atoms. Obtain sulfur atom features to describe the physical characteristics of sulfur atoms and oxygen atom features to describe the physical characteristics of oxygen atoms. Based on the sulfur atom characteristics, the sulfur content to be analyzed, the content data of the sulfur-containing compound, and the second detection data, the mass fraction of sulfur-containing compound molecules that do not contain nitrogen atoms is determined, wherein the second detection data is used to indicate the peak intensity of the sulfur-containing compound molecules. Based on the oxygen atom characteristics, the oxygen content to be analyzed, the content data of the oxygen-containing compound, and the third detection data, the mass fraction of oxygen-containing compound molecules that do not contain nitrogen atoms is determined, wherein the third detection data is used to indicate the peak intensity of the oxygen-containing compound molecules.

5. The crude oil evaluation method according to claim 4, characterized in that, The determination of molecular characteristic data of the crude oil sample based on the molecular composition data includes: Based on the peak area of ​​hydrocarbon compounds indicated by the fourth detection data, they are allocated according to a specified ratio to obtain the mass fraction of saturated hydrocarbons and the mass fraction of aromatic hydrocarbons. Based on the content data of the target monomer compound, the mass fraction of the monomer compound molecules corresponding to the n-alkane, the monocyclic aromatic hydrocarbon and the polycyclic aromatic hydrocarbon are determined respectively. The total mass fraction of saturated hydrocarbon molecules is determined based on the mass fraction of the saturated hydrocarbons and the mass fraction of the monomeric compound molecules corresponding to the n-alkane. The total mass fraction of aromatic hydrocarbon molecules is determined based on the mass fraction of the aromatic hydrocarbons, the mass fraction of the monomeric compound molecules corresponding to the monocyclic aromatic hydrocarbons, and the mass fraction of the monomeric compound molecules corresponding to the polycyclic aromatic hydrocarbons. The mass fraction of hydrocarbon molecules is determined based on the peak intensity of the hydrocarbon molecules indicated by the fourth detection data, the relative molecular mass of the corresponding hydrocarbon molecules, the total mass fraction of the saturated hydrocarbon molecules, and the total mass fraction of the aromatic hydrocarbon molecules.

6. The crude oil evaluation method according to claim 5, characterized in that, The molecular characteristic data includes molecular structure data, which is used to describe the molecular structure of the compound molecule. The quantitative molecular composition data also includes the molecular formula, compound type, and equivalent number of double bonds of the compound molecule. The step of determining the molecular characteristic data of the crude oil sample based on the molecular composition data further includes: Based on the compound type and equivalent number of double bonds of any compound molecule, the compound molecule is matched with a molecular structure library and a side chain library, respectively. The molecular structure library stores one or more molecular core structures, and the side chain library stores one or more side chains. The matching results of the molecular structure library and the side chain library are randomly combined until the quantitative molecular composition data of the combined molecular structures are consistent with the quantitative molecular composition data of the compound molecules. Based on the combined molecular structure, the structure-guided lumped vector of the compound molecule is determined to generate the molecular structure data of the compound molecule.

7. The crude oil evaluation method according to claim 6, characterized in that, The macroscopic physical property data of the crude oil sample includes kinematic viscosity. The determination of the macroscopic physical property data of the crude oil sample based on the molecular characteristic data of the compound molecules and the corresponding property prediction data includes: The first viscosity parameter is calculated based on the target boiling point of the crude oil sample determined by the molecular characteristic data of the crude oil sample. The second viscosity parameter is calculated based on the first viscosity parameter and the characteristic coefficients determined by the molecular characteristic data of the crude oil sample. Based on the target temperature of the crude oil sample, the first viscosity parameter, and the second viscosity parameter, the first kinematic viscosity value of the crude oil sample is calculated, and the objective function is determined by the difference between the first kinematic viscosity value and the specified second kinematic viscosity value. Using a preset partial least squares calculation model, the calculation parameters involved in the first viscosity parameter and the second viscosity parameter are iteratively adjusted to determine the first viscosity parameter and the second viscosity parameter that minimize the objective function, and the first kinematic viscosity value is optimized based on the determined first viscosity parameter and the second viscosity parameter.

8. The crude oil evaluation method according to claim 7, characterized in that, The method further includes: The crude oil sample is cut according to the molecular characteristic data to obtain at least one cut fraction and corresponding fraction characteristic data, wherein the fraction characteristic data includes the mass fraction of the target compound molecules contained in the cut fraction; Based on the mass fraction of the target compound molecule and the target property prediction data of the target compound molecule, the macroscopic physical property data of the cut fraction are determined, wherein the target property prediction data is used to indicate the target physical properties of the target compound molecule.

9. The crude oil evaluation method according to claim 8, characterized in that, The step of cutting the crude oil sample based on the molecular characteristic data to obtain at least one cut fraction and corresponding fraction characteristic data includes: Based on the characteristics of the first cutting interval of the fraction to be cut and the ratio of the first overlapping interval, a lower limit value of the first control parameter is determined. The first control parameter is used to indicate the cutting of the crude oil sample. The first cutting interval characteristics are used to indicate the upper and lower limits of the first cutting interval. The first cutting interval is determined by the target physical properties of the fraction to be cut. The first overlapping interval ratio is used to characterize the ratio of the first overlapping interval between the specified second cutting interval and the first cutting interval to the first cutting interval. The lower limit value of the first cutting interval is not greater than the upper limit value of the second cutting interval. Based on the characteristics of the first cutting interval of the fraction to be cut and the ratio of the second overlapping interval, the upper limit of the first control parameter is determined, wherein the ratio of the second overlapping interval between the specified third cutting interval and the first cutting interval is used to characterize the ratio of the second overlapping interval to the first cutting interval, and the lower limit of the third cutting interval is not greater than the upper limit of the first cutting interval. Based on the characteristics of the first cutting interval of the fraction to be cut, the ratio of the first overlapping interval, and the lower limit of the first control parameter, a lower limit of the second control parameter is determined. The second control parameter is used to indicate the cutting of the crude oil sample. Based on the characteristics of the first cutting interval of the fraction to be cut, the ratio of the second overlapping interval, and the upper limit of the first control parameter, the upper limit of the second control parameter is determined. Based on the lower and upper limits of the first control parameter and the lower and upper limits of the second control parameter, the cutting factor used for cutting is determined; Based on the quantitative molecular composition data of the crude oil sample and the cutting factor, the fractional characteristic data of each cut fraction are determined.

10. A crude oil evaluation device, characterized in that, include: The data acquisition module is used to acquire the molecular composition data of the crude oil sample sent by the analysis equipment. The molecular composition data is used to characterize the content of each compound in the crude oil sample. A molecular composition analysis module is used to determine the molecular characteristic data of the crude oil sample based on the molecular composition data, wherein the molecular characteristic data is used to describe the chemical properties of the compound molecules contained in the compound. The property prediction module is used to predict the properties of the compound molecules based on the molecular feature data, and to obtain property prediction data for each compound molecule. The property prediction data is used to indicate the physical properties of the compound molecules. The macroscopic property determination module is used to determine the macroscopic property data of the crude oil sample based on the molecular characteristic data of the compound molecules and the corresponding property prediction data. The evaluation output module is used to output the evaluation results of the crude oil sample, the evaluation results including the molecular characteristic data and the macroscopic physical property data.

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